{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import os\n",
    "import re\n",
    "import glob\n",
    "import copy\n",
    "import pandas as pd\n",
    "from datetime import datetime\n",
    "\n",
    "with open('../activities_map.json') as f:\n",
    "    activities_map = json.load(f)\n",
    "\n",
    "def is_match_in_activity_list(activity_list, activity):\n",
    "    for activity_name in activity_list:\n",
    "        if activity_name.endswith(activity):\n",
    "            return True\n",
    "\n",
    "    return False\n",
    "\n",
    "def get_activity_coverage(app_name, droidbot_result_path):\n",
    "    states_in_utg = set()\n",
    "    assert os.path.exists(droidbot_result_path), f'{droidbot_result_path} does not exist'\n",
    "    \n",
    "    if os.path.exists(os.path.join(droidbot_result_path, 'utg.js')):\n",
    "        with open(os.path.join(droidbot_result_path, 'utg.js')) as f:\n",
    "            content = f.readlines()\n",
    "        states_in_utg = set()\n",
    "        for line in content:\n",
    "            line = line.strip()\n",
    "            if line.startswith('\"image\":'):\n",
    "                state_tag = line.split('states/screen_')[-1].split('.png')[0]\n",
    "                states_in_utg.add(f'state_{state_tag}.json')\n",
    "\n",
    "    state_files = sorted(glob.glob(os.path.join(droidbot_result_path, 'states', '*.json')))\n",
    "\n",
    "    if len(states_in_utg) > 0:\n",
    "        state_files = [state_file for state_file in state_files if os.path.basename(state_file) in states_in_utg]\n",
    "\n",
    "    covered_activities_so_far = set()\n",
    "    timeline = []\n",
    "    start_time = None\n",
    "    for state_file in state_files:\n",
    "        with open(state_file) as f:\n",
    "            state = json.load(f)\n",
    "        foreground_activity = state['foreground_activity']\n",
    "        if foreground_activity.endswith('}'):\n",
    "            foreground_activity = foreground_activity[:-1]\n",
    "        foreground_activity = foreground_activity.split('/')[-1]\n",
    "        if is_match_in_activity_list(activities_map[app_name], foreground_activity):\n",
    "            covered_activities_so_far.add(foreground_activity)\n",
    "\n",
    "        timestamp = os.path.basename(state_file).removeprefix('state_').removesuffix('.json')\n",
    "        timestamp = datetime.strptime(timestamp, '%Y-%m-%d_%H%M%S')\n",
    "\n",
    "        if start_time is None:\n",
    "            start_time = timestamp\n",
    "\n",
    "        time_offset = (timestamp - start_time).total_seconds()\n",
    "        if time_offset > 7200:\n",
    "            break\n",
    "\n",
    "        timeline.append((timestamp, len(covered_activities_so_far)))\n",
    "\n",
    "    return timeline, len(activities_map[app_name])\n",
    "\n",
    "\n",
    "def get_droidagent_data(droidagent_result_path):\n",
    "    with open(os.path.join(droidagent_result_path, 'exp_data.json')) as f:\n",
    "        data = json.load(f)\n",
    "    return data['visited_activities'], data['app_activities']\n",
    "\n",
    "\"\"\"\n",
    "detect lines like: // Allowing start of Intent { cmp=de.rampro.activitydiary.debug/de.rampro.activitydiary.ui.generic.ManageActivity }\n",
    "\n",
    "extract the activity name in Intent { cmp= [here] }\n",
    "\"\"\"\n",
    "def get_monkey_data(app_name):\n",
    "    output_path = f'../baselines/monkey/{app_name}'\n",
    "    monkey_log_path = glob.glob(os.path.join(output_path, '*/monkey.log'))\n",
    "    assert len(monkey_log_path) == 1\n",
    "\n",
    "    with open(monkey_log_path[0]) as f:\n",
    "        content = f.readlines()\n",
    "\n",
    "    activities = set()\n",
    "    for line in content:\n",
    "        line = line.strip()\n",
    "        if line.startswith('// Allowing start of Intent { cmp='):\n",
    "            activity_name = re.findall(r'cmp=(.*?)\\}', line)[0]\n",
    "            activity_name = activity_name.split('/')[-1].strip()\n",
    "            if is_match_in_activity_list(activities_map[app_name], activity_name):\n",
    "                activities.add(activity_name)\n",
    "\n",
    "    return activities\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "../data/Phonograph 103\n",
      "../baselines/droidbot/Phonograph 558\n",
      "../baselines/humanoid/Phonograph/Phonograph-0.15.0-#112.apk.humandroid.result.emulator-5554.Android7.1#2023-10-09-17-36-46 278\n",
      "../baselines/gptdroid/Phonograph 142\n",
      "../data/collect 119\n",
      "../baselines/droidbot/collect 180\n",
      "../baselines/humanoid/collect/collect_v2023.2.4.apk.humandroid.result.emulator-5554.Android7.1#2023-10-09-05-33-50 116\n",
      "../baselines/gptdroid/collect 16\n",
      "../data/MaterialFB 109\n",
      "../baselines/droidbot/MaterialFB 1158\n",
      "../baselines/humanoid/MaterialFB/MaterialFB.apk.humandroid.result.emulator-5554.Android7.1#2023-10-22-08-55-12 390\n",
      "../baselines/gptdroid/MaterialFB 45\n",
      "../data/commons 125\n",
      "../baselines/droidbot/commons 611\n",
      "../baselines/humanoid/commons/commons-2.11.0-#3244.apk.humandroid.result.emulator-5554.Android7.1#2023-10-22-19-09-33 211\n",
      "../baselines/gptdroid/commons 128\n",
      "../data/osmeditor4android 106\n",
      "../baselines/droidbot/osmeditor4android 339\n",
      "../baselines/humanoid/osmeditor4android/osmeditor4android-debug-#729.apk.humandroid.result.emulator-5554.Android7.1#2023-10-09-15-36-17 198\n",
      "../baselines/gptdroid/osmeditor4android 76\n",
      "../data/AntennaPod 197\n",
      "../baselines/droidbot/AntennaPod 650\n",
      "../baselines/humanoid/AntennaPod/AntennaPod-2.4.0-#5636.apk.humandroid.result.emulator-5554.Android7.1#2023-10-09-23-38-15 272\n",
      "../baselines/gptdroid/AntennaPod 59\n",
      "../data/MyExpenses 156\n",
      "../baselines/droidbot/MyExpenses 1986\n",
      "../baselines/humanoid/MyExpenses/MyExpenses.apk.humandroid.result.emulator-5554.Android7.1#2023-10-22-10-43-49 65\n",
      "../baselines/gptdroid/MyExpenses 170\n",
      "../data/AnkiDroid 143\n",
      "../baselines/droidbot/AnkiDroid 371\n",
      "../baselines/humanoid/AnkiDroid/AnkiDroid-debug-2.10beta3-#6145.apk.humandroid.result.emulator-5554.Android7.1#2023-10-10-18-20-42 206\n",
      "../baselines/gptdroid/AnkiDroid 87\n",
      "../data/OpenTracks 145\n",
      "../baselines/droidbot/OpenTracks 64\n",
      "../baselines/humanoid/OpenTracks/OpenTracks.apk.humandroid.result.emulator-5554.Android7.1#2023-10-22-11-41-45 32\n",
      "../baselines/gptdroid/OpenTracks 181\n",
      "../data/Scarlet-Notes 67\n",
      "../baselines/droidbot/Scarlet-Notes 62\n",
      "../baselines/humanoid/Scarlet-Notes/Scarlet-Notes-6.9.5-#114.apk.humandroid.result.emulator-5554.Android7.1#2023-10-09-19-37-16 427\n",
      "../baselines/gptdroid/Scarlet-Notes 102\n",
      "../data/Markor 94\n",
      "../baselines/droidbot/Markor 547\n",
      "../baselines/humanoid/Markor/markor-2.8.5-#1698.apk.humandroid.result.emulator-5554.Android7.1#2023-10-10-01-38-44 433\n",
      "../baselines/gptdroid/Markor 182\n",
      "../data/openlauncher 71\n",
      "../baselines/droidbot/openlauncher 217\n",
      "../baselines/humanoid/openlauncher/openlauncher-0.3.1-#67.apk.humandroid.result.emulator-5554.Android7.1#2023-10-09-13-35-48 135\n",
      "../baselines/gptdroid/openlauncher 48\n",
      "../data/ActivityDiary 180\n",
      "../baselines/droidbot/ActivityDiary 700\n",
      "../baselines/humanoid/ActivityDiary/ActivityDiary-1.4.0-debug-#285.apk.humandroid.result.emulator-5554.Android7.1#2023-10-10-21-34-37 83\n",
      "../baselines/gptdroid/ActivityDiary 209\n",
      "../data/APhotoManager 67\n",
      "../baselines/droidbot/APhotoManager 161\n",
      "../baselines/humanoid/APhotoManager/APhotoManager.apk.humandroid.result.emulator-5554.Android7.1#2023-10-22-12-48-24 163\n",
      "../baselines/gptdroid/APhotoManager 39\n",
      "../data/Omni-Notes 198\n",
      "../baselines/droidbot/Omni-Notes 575\n",
      "../baselines/humanoid/Omni-Notes/Omni-Notes-6.1.0-#745.apk.humandroid.result.emulator-5554.Android7.1#2023-10-09-11-35-18 252\n",
      "../baselines/gptdroid/Omni-Notes 71\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>App Name</th>\n",
       "      <th>coverage</th>\n",
       "      <th>covered_num</th>\n",
       "      <th>technique</th>\n",
       "      <th>total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Phonograph</td>\n",
       "      <td>0.916667</td>\n",
       "      <td>11</td>\n",
       "      <td>droidagent</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Phonograph</td>\n",
       "      <td>0.583333</td>\n",
       "      <td>7</td>\n",
       "      <td>droidbot</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Phonograph</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>9</td>\n",
       "      <td>humanoid</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Phonograph</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>6</td>\n",
       "      <td>gptdroid</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Phonograph</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>9</td>\n",
       "      <td>monkey</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>Omni-Notes</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>3</td>\n",
       "      <td>droidbot</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>Omni-Notes</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>6</td>\n",
       "      <td>humanoid</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>Omni-Notes</td>\n",
       "      <td>0.416667</td>\n",
       "      <td>5</td>\n",
       "      <td>gptdroid</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>Omni-Notes</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>3</td>\n",
       "      <td>monkey</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>Omni-Notes</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>12</td>\n",
       "      <td>total</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>90 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      App Name  coverage  covered_num   technique  total\n",
       "0   Phonograph  0.916667           11  droidagent     12\n",
       "1   Phonograph  0.583333            7    droidbot     12\n",
       "2   Phonograph  0.750000            9    humanoid     12\n",
       "3   Phonograph  0.500000            6    gptdroid     12\n",
       "4   Phonograph  0.750000            9      monkey     12\n",
       "..         ...       ...          ...         ...    ...\n",
       "85  Omni-Notes  0.250000            3    droidbot     12\n",
       "86  Omni-Notes  0.500000            6    humanoid     12\n",
       "87  Omni-Notes  0.416667            5    gptdroid     12\n",
       "88  Omni-Notes  0.250000            3      monkey     12\n",
       "89  Omni-Notes  1.000000           12       total     12\n",
       "\n",
       "[90 rows x 5 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rows = []\n",
    "\n",
    "for project in os.listdir('../data/'):\n",
    "    if project == 'QuickChat':\n",
    "        continue\n",
    "    if project == '.keep':\n",
    "        continue\n",
    "\n",
    "    path = {\n",
    "        'droidagent': os.path.join('../data/', project),\n",
    "        'droidbot': os.path.join('../baselines/', 'droidbot', project),\n",
    "        'gptdroid': os.path.join('../baselines/', 'gptdroid', project)\n",
    "    }\n",
    "\n",
    "    humanoid_result_path = glob.glob(f'../baselines/humanoid/{project}/*')\n",
    "    assert len(humanoid_result_path) == 1\n",
    "    humanoid_result_path = humanoid_result_path[0]\n",
    "    path['humanoid'] = humanoid_result_path\n",
    "    \n",
    "    num_all_activities = len(activities_map[project])\n",
    "\n",
    "    for technique in ['droidagent', 'droidbot', 'humanoid', 'gptdroid']:\n",
    "        timeline, _ = get_activity_coverage(project, path[technique])\n",
    "        print(path[technique], len(timeline))\n",
    "\n",
    "        rows.append({\n",
    "            'App Name': project,\n",
    "            'coverage': timeline[-1][1]/num_all_activities,\n",
    "            'covered_num': timeline[-1][1],\n",
    "            'technique': technique,\n",
    "            'total': num_all_activities,\n",
    "        })\n",
    "\n",
    "    rows.append({\n",
    "        'App Name': project,\n",
    "        'coverage': len(get_monkey_data(project))/num_all_activities,\n",
    "        'covered_num': len(get_monkey_data(project)),\n",
    "        'technique': 'monkey',\n",
    "        'total': num_all_activities,\n",
    "    })\n",
    "    \n",
    "    rows.append({\n",
    "        'App Name': project,\n",
    "        'coverage': 1,\n",
    "        'covered_num': num_all_activities,\n",
    "        'technique': 'total',\n",
    "        'total': num_all_activities,\n",
    "    })\n",
    "    \n",
    "\n",
    "df = pd.DataFrame(rows)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>technique</th>\n",
       "      <th>droidagent</th>\n",
       "      <th>droidbot</th>\n",
       "      <th>gptdroid</th>\n",
       "      <th>humanoid</th>\n",
       "      <th>monkey</th>\n",
       "      <th>total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>App Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>APhotoManager</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ActivityDiary</th>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AnkiDroid</th>\n",
       "      <td>15</td>\n",
       "      <td>14</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AntennaPod</th>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Markor</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MaterialFB</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MyExpenses</th>\n",
       "      <td>15</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>7</td>\n",
       "      <td>11</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Omni-Notes</th>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OpenTracks</th>\n",
       "      <td>16</td>\n",
       "      <td>7</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>16</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Phonograph</th>\n",
       "      <td>11</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Scarlet-Notes</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>collect</th>\n",
       "      <td>13</td>\n",
       "      <td>12</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>commons</th>\n",
       "      <td>14</td>\n",
       "      <td>11</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>5</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>openlauncher</th>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>osmeditor4android</th>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>12</td>\n",
       "      <td>8</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total</th>\n",
       "      <td>133</td>\n",
       "      <td>87</td>\n",
       "      <td>80</td>\n",
       "      <td>107</td>\n",
       "      <td>101</td>\n",
       "      <td>239</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "technique          droidagent  droidbot  gptdroid  humanoid  monkey  total\n",
       "App Name                                                                  \n",
       "APhotoManager               5         5         4         5       5      9\n",
       "ActivityDiary              10         3         6         5       5     10\n",
       "AnkiDroid                  15        14         6        13      13     22\n",
       "AntennaPod                  4         3         1         5       3     10\n",
       "Markor                      4         4         4         5       5      9\n",
       "MaterialFB                  3         1         3         3       2      4\n",
       "MyExpenses                 15         7        12         7      11     40\n",
       "Omni-Notes                  5         3         5         6       3     12\n",
       "OpenTracks                 16         7        11        10      16     24\n",
       "Phonograph                 11         7         6         9       9     12\n",
       "Scarlet-Notes               3         3         4         3       3      8\n",
       "collect                    13        12         2         9       9     37\n",
       "commons                    14        11         7        12       5     17\n",
       "openlauncher                6         2         3         3       4      7\n",
       "osmeditor4android           9         5         6        12       8     18\n",
       "total                     133        87        80       107     101    239"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_table = df.pivot(index='App Name', columns='technique', values='covered_num').round(2)\n",
    "\n",
    "# add total row\n",
    "df_table.loc['total'] = df_table.sum(axis=0) \n",
    "df_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting Jinja2\n",
      "  Using cached Jinja2-3.1.2-py3-none-any.whl (133 kB)\n",
      "Collecting MarkupSafe>=2.0\n",
      "  Downloading MarkupSafe-2.1.3-cp310-cp310-macosx_10_9_universal2.whl (17 kB)\n",
      "Installing collected packages: MarkupSafe, Jinja2\n",
      "Successfully installed Jinja2-3.1.2 MarkupSafe-2.1.3\n",
      "\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip available: \u001b[0m\u001b[31;49m22.3.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.3.1\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "\\begin{tabular}{lrrrrrr}\n",
      "\\toprule\n",
      "technique & droidagent & droidbot & gptdroid & humanoid & monkey & total \\\\\n",
      "App Name &  &  &  &  &  &  \\\\\n",
      "\\midrule\n",
      "APhotoManager & 5 & 5 & 4 & 5 & 5 & 9 \\\\\n",
      "ActivityDiary & 10 & 3 & 6 & 5 & 5 & 10 \\\\\n",
      "AnkiDroid & 15 & 14 & 6 & 13 & 13 & 22 \\\\\n",
      "AntennaPod & 4 & 3 & 1 & 5 & 3 & 10 \\\\\n",
      "Markor & 4 & 4 & 4 & 5 & 5 & 9 \\\\\n",
      "MaterialFB & 3 & 1 & 3 & 3 & 2 & 4 \\\\\n",
      "MyExpenses & 15 & 7 & 12 & 7 & 11 & 40 \\\\\n",
      "Omni-Notes & 5 & 3 & 5 & 6 & 3 & 12 \\\\\n",
      "OpenTracks & 16 & 7 & 11 & 10 & 16 & 24 \\\\\n",
      "Phonograph & 11 & 7 & 6 & 9 & 9 & 12 \\\\\n",
      "Scarlet-Notes & 3 & 3 & 4 & 3 & 3 & 8 \\\\\n",
      "collect & 13 & 12 & 2 & 9 & 9 & 37 \\\\\n",
      "commons & 14 & 11 & 7 & 12 & 5 & 17 \\\\\n",
      "openlauncher & 6 & 2 & 3 & 3 & 4 & 7 \\\\\n",
      "osmeditor4android & 9 & 5 & 6 & 12 & 8 & 18 \\\\\n",
      "\\bottomrule\n",
      "\\end{tabular}\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%pip install Jinja2\n",
    "print(df.pivot(index='App Name', columns='technique', values='covered_num').round(2).to_latex())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "technique\n",
       "droidagent    0.607589\n",
       "droidbot      0.379749\n",
       "gptdroid      0.400956\n",
       "humanoid      0.514203\n",
       "monkey        0.458128\n",
       "total         1.000000\n",
       "Name: coverage, dtype: float64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# sort project by alphabetical order\n",
    "df = df.sort_values(by=['App Name', 'technique'])\n",
    "df.groupby('technique')['coverage'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting seaborn\n",
      "  Downloading seaborn-0.13.0-py3-none-any.whl (294 kB)\n",
      "\u001b[2K     \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m294.6/294.6 kB\u001b[0m \u001b[31m4.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m[31m6.6 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\n",
      "\u001b[?25hRequirement already satisfied: matplotlib!=3.6.1,>=3.3 in /Users/greenmon/.pyenv/versions/3.10.10/envs/droidagent/lib/python3.10/site-packages (from seaborn) (3.8.0)\n",
      "Requirement already satisfied: pandas>=1.2 in /Users/greenmon/.pyenv/versions/3.10.10/envs/droidagent/lib/python3.10/site-packages (from seaborn) (2.1.2)\n",
      "Requirement already satisfied: numpy!=1.24.0,>=1.20 in /Users/greenmon/.pyenv/versions/3.10.10/envs/droidagent/lib/python3.10/site-packages (from seaborn) (1.26.1)\n",
      "Requirement already satisfied: cycler>=0.10 in /Users/greenmon/.pyenv/versions/3.10.10/envs/droidagent/lib/python3.10/site-packages (from matplotlib!=3.6.1,>=3.3->seaborn) (0.12.1)\n",
      "Requirement already satisfied: pillow>=6.2.0 in /Users/greenmon/.pyenv/versions/3.10.10/envs/droidagent/lib/python3.10/site-packages (from matplotlib!=3.6.1,>=3.3->seaborn) (10.1.0)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in /Users/greenmon/.pyenv/versions/3.10.10/envs/droidagent/lib/python3.10/site-packages (from matplotlib!=3.6.1,>=3.3->seaborn) (2.8.2)\n",
      "Requirement already satisfied: packaging>=20.0 in /Users/greenmon/.pyenv/versions/3.10.10/envs/droidagent/lib/python3.10/site-packages (from matplotlib!=3.6.1,>=3.3->seaborn) (23.2)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in /Users/greenmon/.pyenv/versions/3.10.10/envs/droidagent/lib/python3.10/site-packages (from matplotlib!=3.6.1,>=3.3->seaborn) (1.4.5)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in /Users/greenmon/.pyenv/versions/3.10.10/envs/droidagent/lib/python3.10/site-packages (from matplotlib!=3.6.1,>=3.3->seaborn) (4.43.1)\n",
      "Requirement already satisfied: contourpy>=1.0.1 in /Users/greenmon/.pyenv/versions/3.10.10/envs/droidagent/lib/python3.10/site-packages (from matplotlib!=3.6.1,>=3.3->seaborn) (1.1.1)\n",
      "Requirement already satisfied: pyparsing>=2.3.1 in /Users/greenmon/.pyenv/versions/3.10.10/envs/droidagent/lib/python3.10/site-packages (from matplotlib!=3.6.1,>=3.3->seaborn) (3.1.1)\n",
      "Requirement already satisfied: pytz>=2020.1 in /Users/greenmon/.pyenv/versions/3.10.10/envs/droidagent/lib/python3.10/site-packages (from pandas>=1.2->seaborn) (2023.3.post1)\n",
      "Requirement already satisfied: tzdata>=2022.1 in /Users/greenmon/.pyenv/versions/3.10.10/envs/droidagent/lib/python3.10/site-packages (from pandas>=1.2->seaborn) (2023.3)\n",
      "Requirement already satisfied: six>=1.5 in /Users/greenmon/.pyenv/versions/3.10.10/envs/droidagent/lib/python3.10/site-packages (from python-dateutil>=2.7->matplotlib!=3.6.1,>=3.3->seaborn) (1.16.0)\n",
      "Installing collected packages: seaborn\n",
      "Successfully installed seaborn-0.13.0\n",
      "\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip available: \u001b[0m\u001b[31;49m22.3.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.3.1\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install seaborn\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# set figuresize \n",
    "\n",
    "sns.set(font_scale=1.1)\n",
    "sns.set_style(\"whitegrid\")\n",
    "fig, ax = plt.subplots(figsize=(15, 5))\n",
    "\n",
    "\n",
    "sns.barplot(x=\"App Name\", y=\"coverage\", hue=\"technique\", data=df[df.technique != 'total'], width=0.8, palette=\"Set2\", ax=ax)\n",
    "plt.title('Activity Coverage Comparison', fontsize=15)\n",
    "\n",
    "# rotate xticks\n",
    "plt.xticks(rotation=80)\n",
    "plt.tight_layout()\n",
    "plt.savefig('./figures/RQ1_activity_coverage_comparison.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/n4/5pbkhgg90kn29trx7cx_t10c0000gn/T/ipykernel_94535/1501215937.py:9: FutureWarning: \n",
      "\n",
      "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
      "\n",
      "  ax = sns.barplot(x=\"technique\", y=\"coverage\", data=df_agg, palette='Set2')\n",
      "/var/folders/n4/5pbkhgg90kn29trx7cx_t10c0000gn/T/ipykernel_94535/1501215937.py:11: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.\n",
      "  ax.set_xticklabels(ax.get_xticklabels(), rotation=45)\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 600x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# aggregated \n",
    "\n",
    "df_agg = df[df.technique != 'total'].groupby(['technique'])['coverage'].mean().reset_index()\n",
    "df_agg \n",
    "\n",
    "\n",
    "plt.figure(figsize=(6, 5))\n",
    "plt.title('Activity Coverage Comparison')\n",
    "ax = sns.barplot(x=\"technique\", y=\"coverage\", data=df_agg, palette='Set2')\n",
    "ax.set(xlabel='Technique', ylabel='Coverage')\n",
    "ax.set_xticklabels(ax.get_xticklabels(), rotation=45)\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize activity coverage by time \n",
    "import glob\n",
    "from datetime import datetime\n",
    "import json\n",
    "import pandas as pd\n",
    "\n",
    "def get_activity_coverage_by_time(app_name, result_path, technique='droidagent'):\n",
    "    timeline, num_all_activities = get_activity_coverage(app_name, result_path)\n",
    "\n",
    "    time_snapshots = []\n",
    "    for t, c in timeline:\n",
    "        time_snapshots.append((t, c/num_all_activities))\n",
    "\n",
    "    start_time = time_snapshots[0][0]\n",
    "\n",
    "    rows = []\n",
    "    for t, c in time_snapshots:\n",
    "        time_offset = (t - start_time).total_seconds()\n",
    "        coverage = c\n",
    "\n",
    "        rows.append({\n",
    "            'technique': technique,\n",
    "            'time_offset': time_offset,\n",
    "            'coverage': coverage,\n",
    "        })\n",
    "    \n",
    "    rows.append({\n",
    "        'technique': technique,\n",
    "        'time_offset': 7200,\n",
    "        'coverage': time_snapshots[-1][1],\n",
    "    })\n",
    "\n",
    "    return rows\n",
    "\n",
    "\n",
    "# Visualize activity coverage by time\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "def plot_activity_coverage_by_time(app_name, time_snapshot_df, ax=None):\n",
    "    if ax is None:\n",
    "        fig, ax = plt.subplots(figsize=(10, 4))\n",
    "    \n",
    "    # scale font\n",
    "    sns.set(font_scale=1.2)\n",
    "    sns.set_style(\"whitegrid\", {'axes.grid' : False})\n",
    "    sns.set_palette(\"Set2\")\n",
    "    sns.lineplot(x='time_offset', y='coverage', data=time_snapshot_df, ax=ax, hue='technique')\n",
    "    # set grid none by axis\n",
    "    ax.grid(which='major', axis='both', linestyle='-')\n",
    "    # set legend outside \n",
    "    ax.legend(loc='upper center', bbox_to_anchor=(1.12, 1.03), ncol=1, fontsize=13)\n",
    "    ax.set_title('Activity Coverage by Time (App: {})'.format(app_name))\n",
    "    ax.set_xlim(0, 7200)\n",
    "    ax.set_xlabel('Time (s)', fontsize=15)\n",
    "    ax.set_ylabel('Activity Coverage', fontsize=15)\n",
    "    return ax\n",
    "\n",
    "\n",
    "app_name = 'AnkiDroid'\n",
    "all_rows = []\n",
    "\n",
    "path = {\n",
    "    'droidagent': os.path.join('../data/', app_name),\n",
    "    'droidbot': os.path.join('../baselines/', 'droidbot', app_name),\n",
    "    'gptdroid': os.path.join('../baselines/', 'gptdroid', app_name)\n",
    "}\n",
    "humanoid_result_path = glob.glob(f'../baselines/humanoid/{app_name}/*')\n",
    "assert len(humanoid_result_path) == 1\n",
    "humanoid_result_path = humanoid_result_path[0]\n",
    "path['humanoid'] = humanoid_result_path\n",
    "\n",
    "all_rows.extend(get_activity_coverage_by_time(app_name, path['droidagent'], technique='droidagent'))\n",
    "all_rows.extend(get_activity_coverage_by_time(app_name, path['droidbot'], technique='droidbot'))\n",
    "all_rows.extend(get_activity_coverage_by_time(app_name, path['humanoid'], technique='humanoid'))\n",
    "all_rows.extend(get_activity_coverage_by_time(app_name, path['gptdroid'], technique='gptdroid'))\n",
    "time_snapshot_df = pd.DataFrame(all_rows)\n",
    "\n",
    "# rename technique\n",
    "technique_name_map = {\n",
    "    'droidagent': 'DroidAgent',\n",
    "    'droidbot': 'DroidBot',\n",
    "    'humanoid': 'Humanoid',\n",
    "    'gptdroid': 'GPTDroid',\n",
    "}\n",
    "\n",
    "time_snapshot_df['technique'] = time_snapshot_df['technique'].apply(lambda x: technique_name_map[x])\n",
    "\n",
    "plot_activity_coverage_by_time(app_name, time_snapshot_df)\n",
    "plt.tight_layout()\n",
    "plt.savefig('./figures/RQ1_activity_coverage_by_time.pdf')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "testing-agent",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.10"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
